Non-dimensional net work

The first modification, involving n and is important and affects the Hawthorne-Davis chart. The compressor work is unchanged but the turbine work, and hence the non-dimensional net work NDNW, are increased. The heat supplied term NDHT is also changed. It should be noted here that the assumption n = (n-I-I )/2, used by Horlock and Woods, is not generally valid, except at very low pressure ratios. 

The basic feedforward neural network performs a non-linear transformation of the input data in order to approximate the output data. This net is composed of many simple, locally interacting, computational elements (nodes/neurons), where each node works as a simple processor. The schematic diagram of a single neuron is shown in Fig 1. The input to each i-th neuron consists of a A-dimensional vector X and a single bias (threshold) bj. Each of the input signals Xj is weighted by the appropiate weight Wij, where] = 1- N. 

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